Bayes Theorem can be implemented as an if statement: posterior = [] [observables, unknowns] = simulate_from_model(priors) if observables == observed

Bayes Theorem can be implemented as an if statement: posterior = [] [observables, unknowns] = simulate_from_model(priors) if observables == observed posterior.push(unknowns) posterior now includes random draws from the posterior p(unknowns|observed). This is my favorite explanation of Bayes statistics since it implements Bayes Theorem without math. It also is the underlying intuition behind the probabilistic programming approach to Bayesian statistics. Rubin (1984) has a great explanation: https://twitter.com/tristanzajonc/status/325120025428119552 https://twitter.com/tristanzajonc/status/325120025428119552